Table 3 \(\text {NN}_{RS \& LP}\), \(\text {NN}_{SM}\) and LRs characteristics for the HFDB and the IDB
Architecture | HFDB | IDB | ||
|---|---|---|---|---|
[16 13 12] | [11 9 1] | |||
\(\text {NN}_{RS \& LP}\) | Learning | AUC (%) | 99 | 98 |
Testing | AUC (%) | 84 | 83 | |
CI (%) | [73–95] | [75–91] | ||
ACC (%) | 75 | 76 | ||
\(\text {NN}_{SM}\) | Learning | AUC (%) | 86 | 77 |
Testing | AUC (%) | 83 | 73 | |
CI (%) | [72–94] | [60–87] | ||
ACC (%) | 75 | 67 | ||
LR | Learning | AUC (%) | 89 | 88 |
Testing | AUC (%) | 61 | 77 | |
CI (%) | [46–75] | [68–86] | ||
ACC (%) | 54 | 71 |